If you asked a group of programmers what technology is best for banking software development, the answer would surely be “It depends.” And it’s hard to disagree with it, because the choice of technology depends on the goal it is to achieve. However, taking into account the specificity of the banking industry, stringent security standards and the need to comply with legislation, we have selected 7 technologies that are most often used in banking.


Cobol is a kind of banking IT legend. Anyone who has had contact with this topic at least for a moment associates it as the long-standing foundation of all banking systems. Although nowadays programmers sometimes make fun of this language, it turns out to be wrong. According to Reuters data, as much as 43% of today’s global IT banking systems are created using COBOL, so as you can see, it is still doing quite well. The name COBOL is an acronym for Common Business-Oriented Language and the fact that it works great in achieving business and commercial goals largely explains its use in banking. In addition, COBOL also has a simple and understandable syntax, which means that even a non-technical person can figure out a lot while reading the code.


C # is a high-level object-oriented language developed by Microsoft. Despite the passage of years, it still ranks high in the popularity rankings of programming languages. It works great in creating complex systems and large projects, which in a way explains its place in this article. What distinguishes C # is primarily the fact that it is a technology from Microsoft’s stable, which has at least two big advantages. The first is, of course, the fact that one of the technological giants is behind this language, with a huge budget for development and a lot of support. The second is undoubtedly great backward compatibility (a feature of the software, thanks to which – despite the change in functionality – the new version allows cooperation with the entire environment of the previous version and all its components). In the context of the desired predictability, Microsoft openly defines the direction of development of its technology, thanks to which the changes we will face over the next few years are clear and predictable.


Although C / C ++ was created in the eighties of the last century, its wide range of applications means that many large systems and applications still rely on it. C ++ is distinguished by the fact that it works well for creating complex, multi-level systems due to the specific compiler. The C ++ compiler is type-compliant, so it is more difficult to make errors in code written in C ++, which leads us to greater security of applications written in C ++.


Java is the undisputed queen of banking technology that needs no introduction. It is perfect for projects that require a very high level of security and high efficiency. In addition, it is characterized by high stability and is often used in large implementations. What distinguishes Java is its independence from architecture. The resulting code is independent of the operating system and processor, and is performed by the so-called Java virtual machine that (among other things) translates universal code into code adapted to the specifics of a specific operating system and processor. Such versatility means that wherever it is possible to install a virtual machine, it is also possible to use Java.


JavaScript, or rather the framework of this language, Angular.js, is the most frequently chosen technology when creating the front-end layer of banking applications. JavaScript allows you to build web applications in the SPA – Single Page Application technology, which greatly facilitates the intuitive use of the application. As with other languages, Javascript is a very stable language that has been supported for many years. Considering the fact that front-end technologies change almost overnight and there is a large stratification among them, in the context of stability and predictability, JavaScript seems to be the most optimal choice.


Python is a technology that is most often used in the field of artificial intelligence and machine learning, as well as in data analysis and data science. It is a language of very wide application, and considering that banks are increasingly using AI algorithms, it is not surprising that Python is growing in popularity in this industry. Python is mathematically friendly, and therefore it “gets along” well with financial algorithms. Interestingly, many organizations in the area of ​​fintech and core banking often use Python to analyze data, and taking into account the growing need for technological cooperation between the banking industry and other quasi-financial institutions, it can be expected that its popularity in this area will increase even more.


What is very significant in the case of banking technologies is the fact that long-supported and relatively predictable languages ​​are usually chosen for the development of software and individual components. As banking systems are complex and extensive, banks rarely choose to rewrite them from one technology to another. Therefore, the key is stability and the guarantee that the language will be supported as long as possible, often at the expense of the technological development of the industry. One of the challenges for banking in the coming years will surely be finding a compromise between the use of proven solutions, security and stability, and the possibility of developing and using the latest technologies.